Bo Egardt

Prof. Bo Egardt


Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2019 in Transportation Research Part D: Transport and Environment
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Journal Article
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RBRafael Basso
Rafael Basso
Balázs KulcsárBalázs Kulcsár
Balázs Kulcsár
BEBo Egardt
Bo Egardt
PLPeter Lindroth
Peter Lindroth
ISIvan Sanchez-Diaz
Ivan Sanchez-Diaz

13 November 2017 in IEEE Transactions on Industrial Electronics
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Journal Article
Closed access
Changfu ZouChangfu Zou
Changfu Zou
Xiaosong HuXiaosong Hu
Xiaosong Hu
ZWZhongbao Wei
Zhongbao Wei
TWTorsten Wik
Torsten Wik
BEBo Egardt
Bo Egardt
Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage the batteries. To harness these competing objectives, including safety, lifetime, and charging time, this paper proposes a health-aware fast charging strategy synthesized from electrochemical system modeling and advanced control theory. The battery charging problem is formulated in a linear time-varying model predictive control algorithm. In this algorithm, a control-oriented electrochemical-thermal model is developed to predict the system dynamics. Constraints are explicitly imposed on physically meaningful state variables to protect the battery from hazardous operations. A moving horizon estimation algorithm is employed to monitor battery internal state information. Illustrative results demonstrate that the proposed charging strategy is able to largely reduce the charging time from its benchmarks while ensuring the satisfaction of health-related constraints.

27 October 2017 in IEEE Transactions on Vehicular Technology
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Journal Article
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MPMitra Pourabdollah
Mitra Pourabdollah
BEBo Egardt
Bo Egardt
NMNikolce Murgovski
Nikolce Murgovski
AGAnders Grauers
Anders Grauers
This study investigates the impact of dierent levels of modelling details on the problem of optimizing the total cost of ownership of a fuel-cell hybrid electric vehicle. In this optimization, the objective function is a weighted sum of operational and component costs over a driving cycle. The former includes the consumed hydrogen and electrical energy, and the latter includes the sum of the battery, fuel-cell, and electric-motor costs. Three methods with dierent levels of modelling details are investigated. In the first method, the optimal power split between the two power sources is optimized together with component sizes, while assuming nonlinear loss functions for the components. In the second method, the eciencies of the components are approximated by constant values. In the third method, the problem is simplified further by considering the energy split between battery and fuel-cell over trips in a driving cycle. As shown in the paper, a more detailed model will generally give more accurate results at the price of increased computation time. However, the simplified models can give similar results as the detailed model in most cases. In some problems though, the model simplifications lead to results that dier notably from those obtained by using the detailed model.

1 January 2014 in IFAC Proceedings Volumes
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Journal Article
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MPMitra Pourabdollah
Mitra Pourabdollah
NMNikolce Murgovski
Nikolce Murgovski
AGAnders Grauers
Anders Grauers
BEBo Egardt
Bo Egardt

1 July 2011 in Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles
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Journal Article
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PTP. Templin
P. Templin
BEBo Egardt
Bo Egardt
Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles

1 January 2013 in IFAC Proceedings Volumes
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Journal Article
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LJLars Johannesson
Lars Johannesson
NMNikolce Murgovski
Nikolce Murgovski
SESoren Ebbesen
Soren Ebbesen
BEBo Egardt
Bo Egardt
EGEsteban Gelso
Esteban Gelso
JHJonas Hellgren
Jonas Hellgren